HPE2-N69 Real Question - HPE2-N69 New Cram Materials

Posted 2023-04-18 02:50:16

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HP HPE2-N69 Exam Syllabus Topics:

Topic	Details
Topic 1	Describe the HPE Machine Learning Development Environment software architecture and deployment options Have a conversation with customers about machine learning (ML) and deep learning (DL)
Topic 2	Explain how the Machine Learning Development Environment uses resources and schedules workloads Understand the challenges customers face in training DL models
Topic 3	Qualify customers for HPE Machine Learning Development Environment and System Articulate the business case for HPE Machine Learning Development solutions
Topic 4	Demonstrate running a variety of experiment types on the HPE Machine Learning Development Environment Describe how HPE Machine Learning Development Environment fits in the market

The HP HPE2-N69 certification exam is designed for individuals who want to validate their knowledge and skills in using HPE Cray AI development environment. This certification exam is intended for AI developers, data scientists, and IT professionals who work with HPE AI solutions. The exam measures the candidates' ability to design, configure, and manage HPE Cray AI development environment, including the HPE Cray Programming Environment (CPE), HPE Cray AI Library (CAL), and HPE Cray AI Runtime (CAR).

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The HPE2-N69 certification exam covers a range of topics, including AI model creation, deployment, and management with HPE Cray AI Development Environment. Candidates will need to demonstrate their ability to perform tasks such as designing and building AI models, optimizing AI models for performance, and integrating AI models into existing applications.

HP Using HPE Cray AI Development Environment Sample Questions (Q12-Q17):

NEW QUESTION # 12
A company has recently expanded its ml engineering resources from 5 CPUs 1012 GPUs.
What challenge is likely to continue to stand in the way of accelerating deep learning (DU training?

A. The requirement that the ML team must wait for the IT team to initiate each new training process
B. The complexity of adjusting model code to distribute the training process across multiple GPUs
C. A lack of adequate power and cooling for the GPU-enabled servers
D. A lack of understanding of the DL model architecture by the NL engineering team

Answer: D

NEW QUESTION # 13
The 10 agents in "my-compute-poor nave 8 GPUs each, you want to change an experiment config to run on multiple GPUs at once. What Is a valid setting for "resources_per_trial?

A. 0
B. 1
C. 2
D. 3

Answer: A

Explanation:
The valid setting for "resourcespertrial" for the 10 agents in "my-compute-poor" with 8 GPUs each would be 20, as this would be the total number of GPUs available across all 10 agents. This setting would allow the experiment config to run on multiple GPUs at once.

NEW QUESTION # 14
A trial is running on a GPU slot within a resource pool on HPE Machine Learning Development Environment.
That GPU fails. What happens next?

A. The trial tails, and the ML engineer must restart it manually by re-running the experiment.
B. The concluded reschedules the trial on another available GPU in the pool, and the trial restarts from the state of the latest training workload.
C. The conductor reschedules the trial on another available GPU in the pool, and the trial restarts from the latest checkpoint.
D. The trial fails, and the ML engineer must manually restart it from the latest checkpoint using the WebUI.

Answer: C

NEW QUESTION # 15
You want to set up a simple demo cluster for HPE Machine Learning Development Environment (or the open source Determined Al) on Amazon Web Services (AWS). You plan to use "det deploy" to set up the cluster.
What is one prerequisite?

A. Manually creating the AWS EC2 instance with a PostgreSQL database
B. Recording the name of a valid AWS EC2 keypair
C. installing the NVIDIA Container Toolkit on your local machine
D. Adding Amazon Elastic Kubernetes Services (EKS) to your AWS account

Answer: C

NEW QUESTION # 16
What is a benefit of HPE Machine Learning Development Environment mat tends to resonate with executives?

A. It automatically cleans up data to create better end results.
B. It uses a centralized training architecture that is highly efficient.
C. It helps companies deploy models and generate revenue.
D. It helps DL projects complete faster for a faster ROI.

Answer: D

Explanation:
HPE Machine Learning Development Environment is designed to deliver results more quickly than traditional methods, allowing companies to get a return on their investment sooner and benefit from their DL projects faster. This tends to be a benefit that resonates with executives, as it can help them realize their goals more quickly and efficiently.

NEW QUESTION # 17
......

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